Epigenetic silencing of ferroptosis-regulating genes (PCBP1, GPX4, FTL) in cord blood: identification of novel biomarkers of fetal growth restriction induced by maternal smoking

Epigenetic silencing of ferroptosis-regulating genes (PCBP1, GPX4, FTL) in cord blood: identification of novel biomarkers of fetal growth restriction induced by maternal smoking | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Epigenetic silencing of ferroptosis-regulating genes (PCBP1, GPX4, FTL) in cord blood: identification of novel biomarkers of fetal growth restriction induced by maternal smoking E Barrio, JI Labarta, D Lerma-Puertas, A Gascón-Catalán This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8918607/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Maternal smoking is a leading preventable cause of intrauterine growth restriction (IUGR). While the clinical association is well-established, the molecular mechanisms linking prenatal smoke exposure and reduced fetal growth remain unclear. Ferroptosis, an iron-dependent form of cell death, has been implicated in placental pathology. This study aimed to validate epigenetic alterations in the ferroptosis pathway as potential biomarkers of smoking-induced fetal damage. We analyzed umbilical cord blood from 40 newborns stratified into four groups based on maternal smoking status and birth weight. Methylation levels of ferroptosis-regulating genes (PCBP1, GPX4, FTL) were quantified using MeDIP-qPCR. Maternal smoking induced significant hypermethylation of the iron chaperone PCBP1 (Fold Change = 2.04; p = 1.32×10 − 9) and the antioxidant enzyme GPX4 (p = 2.46×10 − 5). The silencing effect was most pronounced in the "Smoker-Low Birth Weight" group. Additionally, FTL showed hypermethylation associated with low birth weight even in non-smokers (FC = 1.48; p = 0.005), suggesting an adaptive response to growth restriction. Prenatal tobacco exposure triggers targeted epigenetic silencing of the fetal antioxidant and iron-transport machinery. We identify PCBP1 hypermethylation as a highly sensitive biomarker of smoking-induced fetal stress. These findings suggest that ferroptosis is a key mechanism in the pathogenesis of IUGR and highlight potential targets for early detection and preventive strategies. Health sciences/Biomarkers Health sciences/Diseases Biological sciences/Genetics Health sciences/Medical research Biological sciences/Molecular biology Health sciences/Risk factors Ferroptosis Epigenetics Maternal Smoking IUGR DNA Methylation PCBP1 GPX4 Introduction Maternal smoking during pregnancy is a well-documented risk factor that adversely affects fetal development. Exposure to toxic compounds in cigarette smoke increases the likelihood of complications such as preterm birth, low birth weight, and intrauterine growth restriction (IUGR).(1–3) These negative outcomes are associated with oxidative stress, DNA damage, and epigenetic modifications, all of which can have long-term consequences on the health of the offspring (4). One of the key mechanisms by which maternal smoking affects fetal growth is through epigenetic alterations. DNA methylation changes in genes involved in cellular growth, metabolism, and the oxidative stress response have been reported in newborns exposed to tobacco smoke in utero. These modifications can lead to altered gene expression, which in turn can impair critical developmental pathways (5,6). Furthermore, cigarette smoke has been linked to increased oxidative stress, characterized by elevated lipid peroxidation and reduced antioxidant capacity in both the placenta and fetal tissues (7,8). This is evidenced by reduced levels of glutathione (GSH) and glutathione peroxidase (GPx) in the cord blood of infants born to smoking mothers (9). Uncontrolled oxidative stress can contribute to placental dysfunction and adverse perinatal outcomes in newborns with IUGR. While some oxidative stress is necessary for normal fetal growth, excessive levels can lead to placental dysfunction and altered fetal programming (10–11). The ferroptosis pathway, characterized by iron-dependent lipid peroxidation, has emerged as a potential link between oxidative damage and cell death in this context (12–14). However, the specific epigenetic regulation of this pathway in response to maternal smoking remains to be fully elucidated (15–16). The aim of this study is to validate the epigenetic silencing of key ferroptosis-regulating genes and assess their potential as biomarkers for smoking-induced fetal growth restriction. Materials and Methods Study design and population This observational study was conducted at the Lozano Blesa University Clinical Hospital between 2018 and 2019. The study population consisted of 40 newborns. Participants were classified into four groups (n = 10 per group) based on prenatal tobacco exposure and birth weight status: Smoker-LBW: Newborns with low birth weight born ( 10 cigarettes/day during the first trimester. Smoker-NBW: Newborns with adequate (normal) birth weight born to mothers who reported smoking > 10 cigarettes/day. Non-smoker-LBW: Newborns with low birth weight born (< 10th percentile) to mothers who reported no tobacco use. Non-smoker-NBW: Newborns with adequate birth weight born to mothers who reported no tobacco use. Exclusion criteria included maternal diseases known to cause IUGR, preeclampsia, intrauterine infections, fetal malformations, chromosomal alterations, preterm labor, and failure to sign informed consent. Data and sample collection Maternal sociodemographic characteristics and substance use were assessed using an interview-administered questionnaire. Clinical data regarding the course of pregnancy and newborn characteristics were collected from medical records. Umbilical cord blood samples were collected in EDTA tubes immediately after delivery, stored at 4ºC, and transported to the molecular laboratory at the University of Zaragoza School of Medicine. DNA extraction and fragmentation Total genomic DNA was isolated from cord blood using the DNeasy Blood & Tissue Kit (QIAGEN), according to the manufacturer’s instructions. DNA concentration and purity were assessed using a NanoDrop ND-1000. Genomic DNA (11 µg per sample) was fragmented by sonication using a Bioruptor system (Diagenode) to achieve a size range of 200–800 bp. Methylated DNA Immunoprecipitation (MeDIP) MeDIP was performed using an antibody against 5-methylcytidine. For each sample, 5 µg of fragmented genomic DNA was used for immunoprecipitation. Immunoprecipitation was performed by incubating denatured DNA with 5 µg of anti–5-methylcytidine antibody (Diagenode) at 4°C. Blocked anti-mouse magnetic beads were used to collect the complexes. DNA was eluted, purified by phenol–chloroform–isoamyl alcohol extraction, and ethanol precipitated. Bioinformatic analysis (MeDIP-Seq) For the genome-wide discovery phase, bioinformatic processing was performed following the pipeline previously validated by our group [1]. High-quality reads were mapped to the human reference genome (GRCh38/hg38) using Bowtie2. Methylation peaks were identified using MACS2 (q < 0.05). Differentially methylated regions (DMRs) were identified using diffReps (FDR < 0.05, Fold Change ≥ 1.5). MeDIP-qPCR validation To validate the differentially methylated regions, MeDIP-qPCR was performed on the full cohort. Relative enrichment was calculated as Input–IP ratios normalized to negative controls. Statistical analysis Data were analyzed using SPSS Statistics. Differences between groups were assessed using ANOVA or Kruskal-Wallis tests, followed by post-hoc comparisons (Tukey or Dunn). Methylation fold changes were calculated using the 2 − ΔΔCt method. A p-value < 0.05 was considered statistically significant. Results Evaluation of DNA methylation in ferroptosis-related genes This study evaluated DNA methylation levels in three key genes of the ferroptosis pathway (PCBP1, GPX4, and FTL) across four study groups. PCBP1 (Poly(rC) Binding Protein 1) (Table 1 ) The technical validity of the assay was confirmed by comparing the immunoprecipitated fractions (IP) against negative controls. Significant methylation enrichment was observed in the Smoker-LBW group compared to the negative control (Fold Change [FC] = 2.65; p = 0.0012). Analysis of the experimental groups identified maternal smoking as the primary driver of variation. The pooled comparison (Smokers [all] vs. Non-Smokers [all]) revealed highly significant hypermethylation (FC = 2.04; p = 1.32×10 − 9). This difference reached its maximum magnitude in the group of low birth weight neonates born to smoking mothers (Smoker-LBW) compared to the baseline control (Non-Smoker-NBW), showing an FC of 2.05 (p = 6.23×10 − 6). Table 1 Comparison of methylation levels in the PCBP1 gene between study groups Sample Mesure Fold Change p-value SL/NSN Input-IP 2.05 6.23×10⁻⁶ SL/NSL Input-IP 1.73 0.0004 SN + SL/NSN + NSL Input-IP 2.04 1.32×10⁻⁹ SL/SN Input-neg 0.59 0.0131 NSL/NSN Input-neg 2.08 0.0008 SL/NSL IP/neg 2.65 0.0012 SN + SL/NSN + NSL IP/neg 1.58 0.0209 Smoker-LBW (SL): Newborns with Low Birth Weight ( 10 cigarettes/day during the first trimester. Smoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking > 10 cigarettes/day. Non-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers. Non-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group). 2. GPX4 (Glutathione Peroxidase 4) (Table 2 ) The GPX4 gene exhibited a hypermethylation pattern associated with prenatal tobacco exposure. The specificity of the assay was validated by the enrichment ratio (IP/neg) in the Smoker-LBW vs. Non-Smoker-LBW comparison (FC = 2.16; p = 0.0226). Analysis of the pooled groups showed a statistically significant effect of maternal smoking (p = 2.46×10 − 5). When stratifying by neonatal weight, the magnitude of the effect was greatest in the comparison Smoker-LBW / Non-Smoker-NBW, with a hypermethylation FC of 1.99 (p = 0.0004). Furthermore, when comparing exclusively within the low birth weight stratum, smoking was identified as the differential factor (FC = 1.81; p = 0.0046). Table 2 Comparison of methylation levels in the GPX4 gene between study groups Sample Mesure Fold Change p-value SL/NSN Input-IP 1.99 0.0004 SL/NSL Input-IP 1.81 0.0046 SN + SL/NSN + NSL Input-IP 1.79 2.46×10⁻⁵ SL/NSL IP/neg 2.16 0.0226 Smoker-LBW (SL): Newborns with Low Birth Weight ( 10 cigarettes/day during the first trimester. Smoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking > 10 cigarettes/day. Non-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers. Non-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group). 3. FTL (Ferritin Light Chain) (Table 3 ) Unlike the other genes, FTL showed a statistically significant response in the low birth weight group independent of smoking status. In the non-smoking group, low birth weight neonates (Non-Smoker-LBW) exhibited significant hypermethylation compared to those with normal weight (FC = 1.48; p = 0.0055). The combination of maternal smoking and low birth weight (Smoker-LBW / Non-Smoker-NBW) resulted in the highest methylation level for this gene (FC = 1.68; p = 0.0244). Comparative Synthesis MeDIP-qPCR validation established a hierarchy in the epigenetic response: PCBP1 presented the strongest association with smoking (p = 1.32×10 − 9), followed by GPX4 (p = 2.46×10 − 5) and FTL (p = 0.0038). All three genes reached their maximum methylation levels in the combined exposure group (Smoker-LBW). Table 3 Comparison of methylation levels in the FTL gene between study groups Sample Mesure Fold Change p-value NSL/NSN Input-IP 1.48 0.0055 SL/NSN Input-IP 1.68 0.0244 SN + SL/NSN + NSL Input-IP 1.58 0.0038 Smoker-LBW (SL): Newborns with Low Birth Weight ( 10 cigarettes/day during the first trimester. Smoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking > 10 cigarettes/day. Non-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers. Non-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group). Taken together, the MeDIP-qPCR results revealed a consistent hierarchy in the epigenetic response: PCBP1 presented the strongest association with smoking (p = 1.32×10 − 9), followed by GPX4 (p = 2.46×10 − 5) and FTL (p = 0.0038). All three genes reached their maximum methylation levels in the combined exposure group (Smoker-LBW). Discussion Our research group has previously focused its efforts on elucidating the molecular etiology of smoking-associated intrauterine growth restriction. In a preceding study, we preliminarily identified that prenatal tobacco exposure triggers epigenetic modifications in the ferroptosis pathway, affecting fetal development [14]. The present work represents a mechanistic validation and targeted quantification of those initial findings. By utilizing high-precision methodology (MeDIP-qPCR) in a stratified clinical cohort, we do not only confirm the involvement of this pathway but also identify the specific hierarchy of gene silencing: we demonstrate that PCBP1 hypermethylation acts as the dominant molecular event, followed by GPX4 blockade and FTL alteration. These data refine our previous understanding, suggesting that the "epigenetic silencing" of the iron transport and antioxidant defence machinery might be one of the mechanisms through which maternal smoking perpetuates the low birth weight phenotype we have clinically described. Recently, ferroptosis has emerged as a central mechanism in pregnancy complications. While reviews from 2023 and 2025, such as those by Xu et al. [7] and Li et al. [17], have established the theoretical role of ferroptosis in preeclampsia and recurrent miscarriage, our study is among the first to demonstrate its direct implication in tobacco-induced IUGR. Unlike Valdes et al. [18], who used single-nucleus RNA sequencing to describe generalized placental macrophage dysfunction in smokers, our targeted epigenetic approach identifies specific transcriptional silencing as the root cause of this dysfunction. Our data suggest that cellular machinery is not merely "damaged" by smoke but is epigenetically "reprogrammed" to fail in the face of oxidative stress. The most novel and robust finding of our investigation is the identification of PCBP1 (Poly(rC)-binding protein 1) as a highly sensitive epigenetic biomarker in exposed neonates (Fold Change = 2.05; p = 1.32×10 − 9). Classical literature has focused on iron deficiency; however, recent molecular studies like those by Chen et al. [19] indicate that the problem in the toxic placenta is iron mismanagement (labile ferrous iron overload) inducing mitochondrial damage. The intense PCBP1 hypermethylation observed in our study aligns with Chen’s findings, as PCBP1 serves as a crucial chaperone for safe iron trafficking. When PCBP1 expression is downregulated, labile iron remains available to catalyze Fenton reactions, thereby exacerbating lipid peroxidation [20]. From a public health perspective, the statistical significance of PCBP1 positions it as a promising candidate for monitoring the severity of intrauterine environmental insults. Beyond the molecular insights, our results have immediate translational implications for obstetric management. The significant silencing of PCBP1 points to a potential “iron paradox” in smoking pregnancies: the epigenetic suppression of this iron chaperone suggests that unmonitored iron supplementation may be counterproductive, as it could expand the labile iron pool and exacerbate ferroptotic vulnerability in the absence of sufficient sequestration capacity [21]. Furthermore, there is significant variability in iron requirements across the different stages of pregnancy, depending on factors such as baseline iron stores and individual metabolic susceptibility. Evidence suggests that routine iron supplementation may not be universally beneficial and could potentially contribute to adverse outcomes by altering cellular iron homeostasis. This concern is particularly relevant in conditions such as preeclampsia, which shares a common pathophysiology with fetal growth disturbances.(22,23). Furthermore, the concurrent epigenetic downregulation of GPX4 suggests an additional layer of vulnerability, as this selenoenzyme is essential for detoxifying lipid peroxides (24). In this setting, non-invasive and cost-effective lifestyle interventions that enhance dietary Selenium and Vitamin E intake may offer scalable strategies to counteract placental oxidative stress, given that Vitamin E can functionally cooperate with GPX4 to limit lipid peroxidation and ferroptosis. [25–27]. Implementing such low-cost nutritional guidelines, alongside smoking cessation programs enhanced by epigenetic feedback, could significantly reduce the incidence of IUGR. This preventative approach would alleviate the substantial long-term economic burden on the healthcare system associated with neonatal intensive care and chronic metabolic disease management [26]. The primary strength of this study lies in the rigorous stratification of our clinical groups, which enabled us to disentangle the specific effects of maternal smoking from those associated with low birth weight per se. This clinical precision is complemented by the technical rigor of the MeDIP-qPCR validation, which ensured high-resolution quantification of the ferroptosis pathway. While the cohort size (n = 40) is relatively small, the identification of high-magnitude effect sizes and significant epigenetic alterations across multiple key regulators—including PCBP1, GPX4, and FTL—demonstrates the robustness of the observed biological signal. However, this study is not without limitations. Its cross-sectional nature precludes the establishment of temporal causality, and the use of cord blood serves as a non-invasive proxy for placental tissue, which may not fully reflect localized tissue-specific dynamics. Despite these constraints, our findings provide critical mechanistic insights into how maternal smoking disrupts iron metabolism and antioxidant defense systems in the developing fetus. The consistency of the epigenetic response observed across our study groups establishes a compelling foundation for utilizing these ferroptosis-related genes as sentinel biomarkers of intrauterine environmental damage and its associated public health risks. For example, distinguishing which pregnant women would benefit from iron intake and in which cases it would be contraindicated. Future longitudinal studies are warranted to confirm these findings in larger, multi-center cohorts and to assess whether these epigenetic marks on PCBP1 and GPX4 persist into childhood, potentially correlating with long-term metabolic health outcomes Conclusions In summary, this study identifies a novel epigenetic mechanism underlying smoking-induced fetal growth restriction: the targeted methylation-mediated silencing of the ferroptosis-suppressing genes PCBP1, GPX4, and FTL. We demonstrate that maternal smoking compromises the newborn's ability to manage iron and oxidative stress. Specifically, we highlight PCBP1 as a highly significant epigenetic biomarker of tobacco-induced fetal damage. These findings emphasize the urgent need for public health strategies focused on smoking cessation during pregnancy. Furthermore, they support a reassessment of current iron and trace element supplementation strategies during gestation, aiming for a more personalized approach to mitigate the risks of iron-induced oxidative stress. Such advancements could open new avenues for identifying at-risk neonates and improving long-term developmental. Declarations Ethics approval and consent to participate The study was conducted in strict adherence to the ethical principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Clinical Research Ethics Committee of Aragon (CEICA) protocol code PI16/0208. Written informed consent was obtained from all participating mothers. Availability of data and materials Data supporting the findings of this study have been deposited in the Zenodo repository and can be accessed via the following persistent identifier: 10.5281/zenodo.18485259. During the peer-review process, the data can be accessed via the following private link: https://zenodo.org/records/18485259?preview=1&token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImJlMWU0NjZmLWZmMzYtNDMwZC04NzljLTA2MTg3YW JmNDk5ZSIsImRhdGEiOnt9LCJyYW5kb20iOiJlMmIwYTVmNjZhMjFlZDA4N2QwYmE4MzM0ZWYwNjg4NiJ9.zJ7 GeMXkeX59_uQlv192DWVTITPttsJ5caiekSUONh0GzutU_5poaf16bCl9U-1fR4MjobKrE1OvRz6cJoor1Q Competing interests The authors declare that they have no competing interests. Funding This study was supported by Gobierno de Aragon, grant number B19- 23R . Authors' contributions Jose Ignacio Labarta: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Funding acquisition. Ana Gascón-Catalán: Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Formal analysis, Data curation, Conceptualization. Diego Lerma-Puertas: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis. Eva Barrio: Writing – review & editing, Writing – original draft, Validation, Resources, Investigation, Methodology, Formal analysis, Data curation, Conceptualization. All authors read and approved the final manuscript. References Brown DC. Smoking cessation in pregnancy. Can Fam Physician. 1996 Jan;42:102-5. PMID: 8924801; PMCID: PMC2146208. Reeves S, Bernstein I. Effects of maternal tobacco-smoke exposure on fetal growth and neonatal size. Expert Rev Obstet Gynecol. 2008 Nov 1;3(6):719-730. doi: 10.1586/17474108.3.6.719. PMID: 19881889; PMCID: PMC2770192. Beth A. 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French. doi: 10.1016/j.gyobfe.2014.01.008. Epub 2014 Feb 16. PMID: 24533991. Pieczyńska J, Grajeta H. The role of selenium in human conception and pregnancy. J Trace Elem Med Biol. 2015;29:31-38. DOI: 10.1016/j.jtemb.2014.07.003 Traber MG, Head B. Vitamin E: How much is enough, too much and why! Free Radic Biol Med. 2021;176:58-67. DOI: 10.1016/j.freeradbiomed.2021.10.028 Hanson MA, Gluckman PD. Developmental origins of health and disease: new insights. Basic Clin Pharmacol Toxicol. 2008;102(2):90-3 doi: 10.1111/j.1742-7843.2007.00186.x. Hu Q, Zhang Y, Lou H, Ou Z, Liu J, Duan W, et al. GPX4 and vitamin E cooperatively protect hematopoietic stem and progenitor cells from lipid peroxidation and ferroptosis. Cell Death & Disease. 2021;12:706. doi:10.1038/s41419-021-04008-9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 08 Mar, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 20 Feb, 2026 First submitted to journal 19 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8918607","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":604463106,"identity":"0b0e2479-9733-449f-8337-7ef7dca8bc6d","order_by":0,"name":"E Barrio","email":"","orcid":"","institution":"University of Zaragoza","correspondingAuthor":false,"prefix":"","firstName":"E","middleName":"","lastName":"Barrio","suffix":""},{"id":604463107,"identity":"79e7445a-8784-4475-af49-aa8163bdff3b","order_by":1,"name":"JI Labarta","email":"","orcid":"","institution":"Hospital universitario Miguel Servet","correspondingAuthor":false,"prefix":"","firstName":"JI","middleName":"","lastName":"Labarta","suffix":""},{"id":604463108,"identity":"41c62638-4fe9-41c4-9471-29750e4939e7","order_by":2,"name":"D Lerma-Puertas","email":"","orcid":"","institution":"Hospital Clínico Universitario Lozano Blesa","correspondingAuthor":false,"prefix":"","firstName":"D","middleName":"","lastName":"Lerma-Puertas","suffix":""},{"id":604463109,"identity":"5702abe7-2bec-4eba-a4da-a3dfa3fd4cda","order_by":3,"name":"A Gascón-Catalán","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBADOQYGxgbStBiTriWRePX8/Ysff/hRcSd9w+3m5g8/9zDIyRPSLHHjmZlkz5lnuRvuHGww7HnGYGxwgJA1Nw6YMTO2Hc7dcCOxIYHnAEPiBkI65G8c//wZqCXdAKjl4J8DDPXzCTnM4HyPgTRQSwJQS2Mz0JYEBkIOM7zBUwb0y2HDmTcSm5llDkgYbiCkRe788c3AEDssz3cj/fHHNwds5AmGGINEAiqXkHog4CfkjlEwCkbBKBgFAMq3SV5L5qSeAAAAAElFTkSuQmCC","orcid":"","institution":"University of Zaragoza","correspondingAuthor":true,"prefix":"","firstName":"A","middleName":"","lastName":"Gascón-Catalán","suffix":""}],"badges":[],"createdAt":"2026-02-19 15:32:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8918607/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8918607/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104780774,"identity":"3f3a0a71-7a24-4e7a-89cd-4f32084c7ac9","added_by":"auto","created_at":"2026-03-17 07:53:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":441571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8918607/v1/fd33585d-187c-4570-be81-4819943e1489.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epigenetic silencing of ferroptosis-regulating genes (PCBP1, GPX4, FTL) in cord blood: identification of novel biomarkers of fetal growth restriction induced by maternal smoking","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMaternal smoking during pregnancy is a well-documented risk factor that adversely affects fetal development. Exposure to toxic compounds in cigarette smoke increases the likelihood of complications such as preterm birth, low birth weight, and intrauterine growth restriction (IUGR).(1\u0026ndash;3) These negative outcomes are associated with oxidative stress, DNA damage, and epigenetic modifications, all of which can have long-term consequences on the health of the offspring (4).\u003c/p\u003e \u003cp\u003eOne of the key mechanisms by which maternal smoking affects fetal growth is through epigenetic alterations. DNA methylation changes in genes involved in cellular growth, metabolism, and the oxidative stress response have been reported in newborns exposed to tobacco smoke in utero. These modifications can lead to altered gene expression, which in turn can impair critical developmental pathways (5,6). Furthermore, cigarette smoke has been linked to increased oxidative stress, characterized by elevated lipid peroxidation and reduced antioxidant capacity in both the placenta and fetal tissues (7,8). This is evidenced by reduced levels of glutathione (GSH) and glutathione peroxidase (GPx) in the cord blood of infants born to smoking mothers (9). Uncontrolled oxidative stress can contribute to placental dysfunction and adverse perinatal outcomes in newborns with IUGR.\u003c/p\u003e \u003cp\u003eWhile some oxidative stress is necessary for normal fetal growth, excessive levels can lead to placental dysfunction and altered fetal programming (10\u0026ndash;11). The ferroptosis pathway, characterized by iron-dependent lipid peroxidation, has emerged as a potential link between oxidative damage and cell death in this context (12\u0026ndash;14). However, the specific epigenetic regulation of this pathway in response to maternal smoking remains to be fully elucidated (15\u0026ndash;16). The aim of this study is to validate the epigenetic silencing of key ferroptosis-regulating genes and assess their potential as biomarkers for smoking-induced fetal growth restriction.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eStudy design and population This observational study was conducted at the Lozano Blesa University Clinical Hospital between 2018 and 2019. The study population consisted of 40 newborns. Participants were classified into four groups (n\u0026thinsp;=\u0026thinsp;10 per group) based on prenatal tobacco exposure and birth weight status:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSmoker-LBW: Newborns with low birth weight born (\u0026lt;\u0026thinsp;10th percentile) to mothers who reported smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day during the first trimester.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSmoker-NBW: Newborns with adequate (normal) birth weight born to mothers who reported smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNon-smoker-LBW: Newborns with low birth weight born (\u0026lt;\u0026thinsp;10th percentile) to mothers who reported no tobacco use.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNon-smoker-NBW: Newborns with adequate birth weight born to mothers who reported no tobacco use.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eExclusion criteria included maternal diseases known to cause IUGR, preeclampsia, intrauterine infections, fetal malformations, chromosomal alterations, preterm labor, and failure to sign informed consent.\u003c/p\u003e \u003cp\u003eData and sample collection Maternal sociodemographic characteristics and substance use were assessed using an interview-administered questionnaire. Clinical data regarding the course of pregnancy and newborn characteristics were collected from medical records. Umbilical cord blood samples were collected in EDTA tubes immediately after delivery, stored at 4\u0026ordm;C, and transported to the molecular laboratory at the University of Zaragoza School of Medicine.\u003c/p\u003e \u003cp\u003eDNA extraction and fragmentation Total genomic DNA was isolated from cord blood using the DNeasy Blood \u0026amp; Tissue Kit (QIAGEN), according to the manufacturer\u0026rsquo;s instructions. DNA concentration and purity were assessed using a NanoDrop ND-1000. Genomic DNA (11 \u0026micro;g per sample) was fragmented by sonication using a Bioruptor system (Diagenode) to achieve a size range of 200\u0026ndash;800 bp.\u003c/p\u003e \u003cp\u003eMethylated DNA Immunoprecipitation (MeDIP) MeDIP was performed using an antibody against 5-methylcytidine. For each sample, 5 \u0026micro;g of fragmented genomic DNA was used for immunoprecipitation. Immunoprecipitation was performed by incubating denatured DNA with 5 \u0026micro;g of anti\u0026ndash;5-methylcytidine antibody (Diagenode) at 4\u0026deg;C. Blocked anti-mouse magnetic beads were used to collect the complexes. DNA was eluted, purified by phenol\u0026ndash;chloroform\u0026ndash;isoamyl alcohol extraction, and ethanol precipitated.\u003c/p\u003e \u003cp\u003eBioinformatic analysis (MeDIP-Seq) For the genome-wide discovery phase, bioinformatic processing was performed following the pipeline previously validated by our group [1]. High-quality reads were mapped to the human reference genome (GRCh38/hg38) using Bowtie2. Methylation peaks were identified using MACS2 (q\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Differentially methylated regions (DMRs) were identified using diffReps (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fold Change\u0026thinsp;\u0026ge;\u0026thinsp;1.5).\u003c/p\u003e \u003cp\u003eMeDIP-qPCR validation To validate the differentially methylated regions, MeDIP-qPCR was performed on the full cohort. Relative enrichment was calculated as Input\u0026ndash;IP ratios normalized to negative controls.\u003c/p\u003e \u003cp\u003eStatistical analysis Data were analyzed using SPSS Statistics. Differences between groups were assessed using ANOVA or Kruskal-Wallis tests, followed by post-hoc comparisons (Tukey or Dunn). Methylation fold changes were calculated using the 2\u0026thinsp;\u0026minus;\u0026thinsp;ΔΔCt method. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eEvaluation of DNA methylation in ferroptosis-related genes This study evaluated DNA methylation levels in three key genes of the ferroptosis pathway (PCBP1, GPX4, and FTL) across four study groups.\u003c/p\u003e \u003cp\u003ePCBP1 (Poly(rC) Binding Protein 1) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe technical validity of the assay was confirmed by comparing the immunoprecipitated fractions (IP) against negative controls. Significant methylation enrichment was observed in the Smoker-LBW group compared to the negative control (Fold Change [FC]\u0026thinsp;=\u0026thinsp;2.65; p\u0026thinsp;=\u0026thinsp;0.0012).\u003c/p\u003e \u003cp\u003eAnalysis of the experimental groups identified maternal smoking as the primary driver of variation. The pooled comparison (Smokers [all] vs. Non-Smokers [all]) revealed highly significant hypermethylation (FC\u0026thinsp;=\u0026thinsp;2.04; p\u0026thinsp;=\u0026thinsp;1.32\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;9). This difference reached its maximum magnitude in the group of low birth weight neonates born to smoking mothers (Smoker-LBW) compared to the baseline control (Non-Smoker-NBW), showing an FC of 2.05 (p\u0026thinsp;=\u0026thinsp;6.23\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;6).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of methylation levels in the PCBP1 gene between study groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMesure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.23\u0026times;10⁻⁶\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u0026thinsp;+\u0026thinsp;SL/NSN\u0026thinsp;+\u0026thinsp;NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32\u0026times;10⁻⁹\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/SN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-neg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSL/NSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-neg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIP/neg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u0026thinsp;+\u0026thinsp;SL/NSN\u0026thinsp;+\u0026thinsp;NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIP/neg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSmoker-LBW (SL): Newborns with Low Birth Weight (\u0026lt;\u0026thinsp;10th percentile) born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day during the first trimester.\u003c/p\u003e \u003cp\u003eSmoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day.\u003c/p\u003e \u003cp\u003eNon-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers.\u003c/p\u003e \u003cp\u003eNon-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group).\u003c/p\u003e \u003cp\u003e2. GPX4 (Glutathione Peroxidase 4) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe GPX4 gene exhibited a hypermethylation pattern associated with prenatal tobacco exposure. The specificity of the assay was validated by the enrichment ratio (IP/neg) in the Smoker-LBW vs. Non-Smoker-LBW comparison (FC\u0026thinsp;=\u0026thinsp;2.16; p\u0026thinsp;=\u0026thinsp;0.0226).\u003c/p\u003e \u003cp\u003eAnalysis of the pooled groups showed a statistically significant effect of maternal smoking (p\u0026thinsp;=\u0026thinsp;2.46\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5). When stratifying by neonatal weight, the magnitude of the effect was greatest in the comparison Smoker-LBW / Non-Smoker-NBW, with a hypermethylation FC of 1.99 (p\u0026thinsp;=\u0026thinsp;0.0004). Furthermore, when comparing exclusively within the low birth weight stratum, smoking was identified as the differential factor (FC\u0026thinsp;=\u0026thinsp;1.81; p\u0026thinsp;=\u0026thinsp;0.0046).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of methylation levels in the GPX4 gene between study groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMesure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u0026thinsp;+\u0026thinsp;SL/NSN\u0026thinsp;+\u0026thinsp;NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.46\u0026times;10⁻⁵\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIP/neg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSmoker-LBW (SL): Newborns with Low Birth Weight (\u0026lt;\u0026thinsp;10th percentile) born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day during the first trimester.\u003c/p\u003e \u003cp\u003eSmoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day.\u003c/p\u003e \u003cp\u003eNon-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers.\u003c/p\u003e \u003cp\u003eNon-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group).\u003c/p\u003e \u003cp\u003e3. FTL (Ferritin Light Chain) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eUnlike the other genes, FTL showed a statistically significant response in the low birth weight group independent of smoking status. In the non-smoking group, low birth weight neonates (Non-Smoker-LBW) exhibited significant hypermethylation compared to those with normal weight (FC\u0026thinsp;=\u0026thinsp;1.48; p\u0026thinsp;=\u0026thinsp;0.0055). The combination of maternal smoking and low birth weight (Smoker-LBW / Non-Smoker-NBW) resulted in the highest methylation level for this gene (FC\u0026thinsp;=\u0026thinsp;1.68; p\u0026thinsp;=\u0026thinsp;0.0244).\u003c/p\u003e \u003cp\u003eComparative Synthesis MeDIP-qPCR validation established a hierarchy in the epigenetic response: PCBP1 presented the strongest association with smoking (p\u0026thinsp;=\u0026thinsp;1.32\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;9), followed by GPX4 (p\u0026thinsp;=\u0026thinsp;2.46\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5) and FTL (p\u0026thinsp;=\u0026thinsp;0.0038). All three genes reached their maximum methylation levels in the combined exposure group (Smoker-LBW).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of methylation levels in the FTL gene between study groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMesure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSL/NSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL/NSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSN\u0026thinsp;+\u0026thinsp;SL/NSN\u0026thinsp;+\u0026thinsp;NSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput-IP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSmoker-LBW (SL): Newborns with Low Birth Weight (\u0026lt;\u0026thinsp;10th percentile) born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day during the first trimester.\u003c/p\u003e \u003cp\u003eSmoker-NBW(SN): Newborns with Normal Birth Weight born to mothers smoking\u0026thinsp;\u0026gt;\u0026thinsp;10 cigarettes/day.\u003c/p\u003e \u003cp\u003eNon-smoker-LBW (NSL): Newborns with Low Birth Weight born to non-smoking mothers.\u003c/p\u003e \u003cp\u003eNon-smoker-NBW (NSN): Newborns with Normal Birth Weight born to non-smoking mothers (Control Group).\u003c/p\u003e \u003cp\u003eTaken together, the MeDIP-qPCR results revealed a consistent hierarchy in the epigenetic response: PCBP1 presented the strongest association with smoking (p\u0026thinsp;=\u0026thinsp;1.32\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;9), followed by GPX4 (p\u0026thinsp;=\u0026thinsp;2.46\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5) and FTL (p\u0026thinsp;=\u0026thinsp;0.0038). All three genes reached their maximum methylation levels in the combined exposure group (Smoker-LBW).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur research group has previously focused its efforts on elucidating the molecular etiology of smoking-associated intrauterine growth restriction. In a preceding study, we preliminarily identified that prenatal tobacco exposure triggers epigenetic modifications in the ferroptosis pathway, affecting fetal development [14]. The present work represents a mechanistic validation and targeted quantification of those initial findings. By utilizing high-precision methodology (MeDIP-qPCR) in a stratified clinical cohort, we do not only confirm the involvement of this pathway but also identify the specific hierarchy of gene silencing: we demonstrate that PCBP1 hypermethylation acts as the dominant molecular event, followed by GPX4 blockade and FTL alteration. These data refine our previous understanding, suggesting that the \"epigenetic silencing\" of the iron transport and antioxidant defence machinery might be one of the mechanisms through which maternal smoking perpetuates the low birth weight phenotype we have clinically described.\u003c/p\u003e \u003cp\u003eRecently, ferroptosis has emerged as a central mechanism in pregnancy complications. While reviews from 2023 and 2025, such as those by Xu et al. [7] and Li et al. [17], have established the theoretical role of ferroptosis in preeclampsia and recurrent miscarriage, our study is among the first to demonstrate its direct implication in tobacco-induced IUGR. Unlike Valdes et al. [18], who used single-nucleus RNA sequencing to describe generalized placental macrophage dysfunction in smokers, our targeted epigenetic approach identifies specific transcriptional silencing as the root cause of this dysfunction. Our data suggest that cellular machinery is not merely \"damaged\" by smoke but is epigenetically \"reprogrammed\" to fail in the face of oxidative stress.\u003c/p\u003e \u003cp\u003eThe most novel and robust finding of our investigation is the identification of PCBP1 (Poly(rC)-binding protein 1) as a highly sensitive epigenetic biomarker in exposed neonates (Fold Change\u0026thinsp;=\u0026thinsp;2.05; p\u0026thinsp;=\u0026thinsp;1.32\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;9). Classical literature has focused on iron deficiency; however, recent molecular studies like those by Chen et al. [19] indicate that the problem in the toxic placenta is iron mismanagement (labile ferrous iron overload) inducing mitochondrial damage. The intense PCBP1 hypermethylation observed in our study aligns with Chen\u0026rsquo;s findings, as PCBP1 serves as a crucial chaperone for safe iron trafficking. When PCBP1 expression is downregulated, labile iron remains available to catalyze Fenton reactions, thereby exacerbating lipid peroxidation [20]. From a public health perspective, the statistical significance of PCBP1 positions it as a promising candidate for monitoring the severity of intrauterine environmental insults.\u003c/p\u003e \u003cp\u003eBeyond the molecular insights, our results have immediate translational implications for obstetric management. The significant silencing of PCBP1 points to a potential \u0026ldquo;iron paradox\u0026rdquo; in smoking pregnancies: the epigenetic suppression of this iron chaperone suggests that unmonitored iron supplementation may be counterproductive, as it could expand the labile iron pool and exacerbate ferroptotic vulnerability in the absence of sufficient sequestration capacity [21]. Furthermore, there is significant variability in iron requirements across the different stages of pregnancy, depending on factors such as baseline iron stores and individual metabolic susceptibility. Evidence suggests that routine iron supplementation may not be universally beneficial and could potentially contribute to adverse outcomes by altering cellular iron homeostasis. This concern is particularly relevant in conditions such as preeclampsia, which shares a common pathophysiology with fetal growth disturbances.(22,23).\u003c/p\u003e \u003cp\u003eFurthermore, the concurrent epigenetic downregulation of GPX4 suggests an additional layer of vulnerability, as this selenoenzyme is essential for detoxifying lipid peroxides (24). In this setting, non-invasive and cost-effective lifestyle interventions that enhance dietary Selenium and Vitamin E intake may offer scalable strategies to counteract placental oxidative stress, given that Vitamin E can functionally cooperate with GPX4 to limit lipid peroxidation and ferroptosis. [25\u0026ndash;27]. Implementing such low-cost nutritional guidelines, alongside smoking cessation programs enhanced by epigenetic feedback, could significantly reduce the incidence of IUGR. This preventative approach would alleviate the substantial long-term economic burden on the healthcare system associated with neonatal intensive care and chronic metabolic disease management [26].\u003c/p\u003e \u003cp\u003eThe primary strength of this study lies in the rigorous stratification of our clinical groups, which enabled us to disentangle the specific effects of maternal smoking from those associated with low birth weight per se. This clinical precision is complemented by the technical rigor of the MeDIP-qPCR validation, which ensured high-resolution quantification of the ferroptosis pathway. While the cohort size (n\u0026thinsp;=\u0026thinsp;40) is relatively small, the identification of high-magnitude effect sizes and significant epigenetic alterations across multiple key regulators\u0026mdash;including PCBP1, GPX4, and FTL\u0026mdash;demonstrates the robustness of the observed biological signal.\u003c/p\u003e \u003cp\u003eHowever, this study is not without limitations. Its cross-sectional nature precludes the establishment of temporal causality, and the use of cord blood serves as a non-invasive proxy for placental tissue, which may not fully reflect localized tissue-specific dynamics. Despite these constraints, our findings provide critical mechanistic insights into how maternal smoking disrupts iron metabolism and antioxidant defense systems in the developing fetus.\u003c/p\u003e \u003cp\u003eThe consistency of the epigenetic response observed across our study groups establishes a compelling foundation for utilizing these ferroptosis-related genes as sentinel biomarkers of intrauterine environmental damage and its associated public health risks. For example, distinguishing which pregnant women would benefit from iron intake and in which cases it would be contraindicated. Future longitudinal studies are warranted to confirm these findings in larger, multi-center cohorts and to assess whether these epigenetic marks on PCBP1 and GPX4 persist into childhood, potentially correlating with long-term metabolic health outcomes\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study identifies a novel epigenetic mechanism underlying smoking-induced fetal growth restriction: the targeted methylation-mediated silencing of the ferroptosis-suppressing genes PCBP1, GPX4, and FTL. We demonstrate that maternal smoking compromises the newborn's ability to manage iron and oxidative stress. Specifically, we highlight PCBP1 as a highly significant epigenetic biomarker of tobacco-induced fetal damage. These findings emphasize the urgent need for public health strategies focused on smoking cessation during pregnancy. Furthermore, they support a reassessment of current iron and trace element supplementation strategies during gestation, aiming for a more personalized approach to mitigate the risks of iron-induced oxidative stress. Such advancements could open new avenues for identifying at-risk neonates and improving long-term developmental.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate The study was conducted in strict adherence to the ethical principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Clinical Research Ethics Committee of Aragon (CEICA) protocol code PI16/0208. Written informed consent was obtained from all participating mothers.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eData supporting the findings of this study have been deposited in the Zenodo repository and can be accessed via the following persistent identifier: 10.5281/zenodo.18485259. During the peer-review process, the data can be accessed via the following private link: \u0026nbsp; \u0026nbsp;https://zenodo.org/records/18485259?preview=1\u0026amp;token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImJlMWU0NjZmLWZmMzYtNDMwZC04NzljLTA2MTg3YW\u003cbr/\u003eJmNDk5ZSIsImRhdGEiOnt9LCJyYW5kb20iOiJlMmIwYTVmNjZhMjFlZDA4N2QwYmE4MzM0ZWYwNjg4NiJ9.zJ7\u003cbr/\u003eGeMXkeX59_uQlv192DWVTITPttsJ5caiekSUONh0GzutU_5poaf16bCl9U-1fR4MjobKrE1OvRz6cJoor1Q\u003c/p\u003e\n\u003cp\u003eCompeting interests The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding This study was supported by Gobierno de Aragon, grant number B19- 23R .\u003c/p\u003e\n\u003cp\u003eAuthors' contributions Jose Ignacio Labarta: Writing – review \u0026amp; editing, Writing – original\u0026nbsp; draft, Supervision, Resources, Project administration, Funding acquisition. Ana Gascón-Catalán: Writing – review \u0026amp; editing, Writing – original draft, Validation, Supervision, Methodology, Formal analysis, Data curation, Conceptualization. Diego Lerma-Puertas: \u0026nbsp;Writing – review \u0026amp; editing, Writing – original draft, Methodology, Investigation, Formal analysis. Eva Barrio: \u0026nbsp;Writing – review \u0026amp; editing, Writing – original draft, Validation, Resources, Investigation, Methodology, Formal analysis, Data curation, Conceptualization. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrown DC. Smoking cessation in pregnancy. Can Fam Physician. 1996 Jan;42:102-5. PMID: 8924801; PMCID: PMC2146208.\u003c/li\u003e\n\u003cli\u003eReeves S, Bernstein I. Effects of maternal tobacco-smoke exposure on fetal growth and neonatal size. Expert Rev Obstet Gynecol. 2008 Nov 1;3(6):719-730. doi: 10.1586/17474108.3.6.719. PMID: 19881889; PMCID: PMC2770192.\u003c/li\u003e\n\u003cli\u003eBeth A. Bailey, Haley Kopkau, Katherine Nadolski, Phoebe Dodge,Impact of in utero tobacco exposure on fetal growth: Amount of exposure and second trimester fetal growth measurements, Neurotoxicology and Teratology, 102,2024, 107334,ISSN 0892-0362, https://doi.org/10.1016/j.ntt.2024.107334.\u003c/li\u003e\n\u003cli\u003ede Assis KR, Ladeira MS, Bueno RC, Dos Santos BF, Dalben I, Salvadori DM. Genotoxicity of cigarette smoking in maternal and newborn lymphocytes. Mutat Res. 2009 Sep-Oct;679(1-2):72-8. doi: 10.1016/j.mrgentox.2009.02.006. Epub 2009 Feb 11. PMID: 19773089.\u003c/li\u003e\n\u003cli\u003eTsiigkaris A, Karantza M. Smoke signals in the genome: Epigenetic consequences of parental tobacco exposure. Biomed Rep. 2025;22(3):58. doi: 10.3892/br.2025.2024.\u003c/li\u003e\n\u003cli\u003eSuter MA, Anders AM, Aagaard KM. 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Antioxidants. 2021 Nov 24;10(12):1866.\u003c/li\u003e\n\u003cli\u003eStone WL, Bailey B, Khraisha N. The pathophysiology of smoking during pregnancy: a systems biology approach. Front Biosci (Elite Ed). 2014 Jun 1;6(2):318-28. doi: 10.2741/e708. PMID: 24896208.\u003c/li\u003e\n\u003cli\u003eSimon-Szab\u0026oacute; Z, Nemes-Nagy E, D\u0026eacute;nes L, Szab\u0026oacute; B. The Influence of Oxidative Stress-Related Factors on Pregnancy and Neonatal Outcomes. Journal of Interdisciplinary Medicine 2020;5(4):146-151 DOI: 10.2478/jim-2020-0033\u003c/li\u003e\n\u003cli\u003ePineda-Caplliure, A. \u0026amp; codo\u0026ntilde;er-franch, Pilar. Oxidative stress in intrauterine growth retardation. Journal of Pediatric Biochemistry.2013; 3. 137-142. Doi:10.3233/JPB-130086.\u003c/li\u003e\n\u003cli\u003eRochette L, Dogon G, Rigal E, Zeller M, Cottin Y, Vergely C. Lipid Peroxidation and Iron Metabolism: Two Corner Stones in the Homeostasis Control of Ferroptosis. 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Basic Clin Pharmacol Toxicol. 2008;102(2):90-3 doi: 10.1111/j.1742-7843.2007.00186.x.\u003c/li\u003e\n\u003cli\u003eHu Q, Zhang Y, Lou H, Ou Z, Liu J, Duan W, et al. \u003cstrong\u003eGPX4 and vitamin E cooperatively protect hematopoietic stem and progenitor cells from lipid peroxidation and ferroptosis.\u003c/strong\u003e\u003cem\u003eCell Death \u0026amp; Disease.\u003c/em\u003e 2021;12:706. doi:10.1038/s41419-021-04008-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ferroptosis, Epigenetics, Maternal Smoking, IUGR, DNA Methylation, PCBP1, GPX4","lastPublishedDoi":"10.21203/rs.3.rs-8918607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8918607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMaternal smoking is a leading preventable cause of intrauterine growth restriction (IUGR). While the clinical association is well-established, the molecular mechanisms linking prenatal smoke exposure and reduced fetal growth remain unclear. Ferroptosis, an iron-dependent form of cell death, has been implicated in placental pathology. This study aimed to validate epigenetic alterations in the ferroptosis pathway as potential biomarkers of smoking-induced fetal damage. We analyzed umbilical cord blood from 40 newborns stratified into four groups based on maternal smoking status and birth weight. Methylation levels of ferroptosis-regulating genes (PCBP1, GPX4, FTL) were quantified using MeDIP-qPCR. Maternal smoking induced significant hypermethylation of the iron chaperone PCBP1 (Fold Change\u0026thinsp;=\u0026thinsp;2.04; p\u0026thinsp;=\u0026thinsp;1.32\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;9) and the antioxidant enzyme GPX4 (p\u0026thinsp;=\u0026thinsp;2.46\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5). The silencing effect was most pronounced in the \"Smoker-Low Birth Weight\" group. Additionally, FTL showed hypermethylation associated with low birth weight even in non-smokers (FC\u0026thinsp;=\u0026thinsp;1.48; p\u0026thinsp;=\u0026thinsp;0.005), suggesting an adaptive response to growth restriction. Prenatal tobacco exposure triggers targeted epigenetic silencing of the fetal antioxidant and iron-transport machinery. We identify PCBP1 hypermethylation as a highly sensitive biomarker of smoking-induced fetal stress. These findings suggest that ferroptosis is a key mechanism in the pathogenesis of IUGR and highlight potential targets for early detection and preventive strategies.\u003c/p\u003e","manuscriptTitle":"Epigenetic silencing of ferroptosis-regulating genes (PCBP1, GPX4, FTL) in cord blood: identification of novel biomarkers of fetal growth restriction induced by maternal smoking","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-12 17:22:40","doi":"10.21203/rs.3.rs-8918607/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-09T02:22:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T05:28:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T05:27:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-19T13:47:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f13ca5e7-83ec-42c1-9778-1c341401e0d3","owner":[],"postedDate":"March 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":64412522,"name":"Health sciences/Biomarkers"},{"id":64412523,"name":"Health sciences/Diseases"},{"id":64412524,"name":"Biological sciences/Genetics"},{"id":64412525,"name":"Health sciences/Medical research"},{"id":64412526,"name":"Biological sciences/Molecular biology"},{"id":64412527,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-03-12T17:22:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-12 17:22:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8918607","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8918607","identity":"rs-8918607","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}